A new artificial intelligence method used various factors, including pancreas health and fat levels, to determine patients at risk for developing type 2 diabetes.
Researchers from the National Institutes of Health Clinical Center developed a new artificial intelligence (AI) model that analyzed various factors relating to pancreas health and fat levels using non-contrast abdominal CT images to detect type 2 diabetes risk.
The study, which was published in Radiology, evaluated 8,992 patients, of which 572 had type 2 diabetes mellitus, and 1,880 had dysglycemia. All patient screenings occurred between 2004 and 2016.
To build the model researchers used 471 images obtained from various datasets. They divided the photos into three categories: 424 for training, 8 for validation, and 39 for test sets.